报告题目：Analyzing Twitter Data via Smoothing Spline ANOVA

时间：2015年12月21（星期一）14：30-15：30

地点：学院南路校区，学术会堂603

报告人：Professor Ping Ma, Department of Statistics, University of Georgia

报告摘要：

Social media, e.g., Facebook and Twitter, have drastically changed personal information generation, distribution, and exchange. Massive streams of social media data provide alternatives to traditional data collection approaches like questionnaires or interviews for understanding personal opinions and observations and, thus, are increasingly investigated by researchers in many domains. Many social media has the location and time stamps associated with the posted information, and thus is regarded as a major spatiotemporal data source. Twitter, for example, introduced location-based services in 2010, which has opened new windows for studying spatiotemporal trends in social media data.

In this talk, I present a smoothing spline ANOVA approach to analyze Twitter data. This talk is based on a joint work with Nate Helwig, YizhaoGao, and Shaowen Wang.

报告人简介：

马平教授为威斯尼斯人“手拉手”项目特聘教授，佐治亚大学（UGA）统计系副教授，美国普渡大学统计学博士，哈佛大学统计系博士后。马平教授在非参数统计、数据建模、超大样本统计等方面有着很深的理论造诣，在高水平学术杂志上发表论文20余篇，承担9项美国国家科学基金（NSF）科研项目。曾获得Canadian Journal of Statistics优秀论文奖、美国自然科学基金CAREER 奖、University of Illinois优秀教师称号。同时还担任Journal of the American Statistical Association等多个国际著名统计学期刊的副主编。

[编辑]：孙颖